代码搜索：classifiers
找到约 2,305 项符合「classifiers」的源代码
代码结果 2,305
www.eeworm.com/read/128684/5980353
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/483114/6609755
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/128193/14311484
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/222301/14697800
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/13911/286927
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/411379/2188990
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/111603/15509356
m smosvctutor.m
function tutor = smosvctutor(arg)
% SMOSVCTUTOR
%
% Construct a tutor object for training support vector classifiers using the
% sequential minimal optimisation algorithm.
%
% Examples:
%
%
www.eeworm.com/read/397106/8067840
m classifierwrapper.m
% trains the classifier to distinguish between pairs of classes, computes
% majority vote, and labels accordingly.
% This is useful for classifiers such as Linear Discriminants, LS,
% perceptron etc.
www.eeworm.com/read/250585/4429362
entries
D/associations////
D/attributeSelection////
D/classifiers////
D/clusterers////
D/core////
D/datagenerators////
D/estimators////
D/experiment////
D/filters////
D/gui////
www.eeworm.com/read/143706/12850015
m wekaclassify.m
function [Y_compute, Y_prob] = WekaClassify(classifier, para, X_train, Y_train, X_test, Y_test, num_class)
global temp_train_file temp_test_file temp_output_file temp_model_file;
[class_set,